7 papers
VIHD: Visual Intervention-based Hallucination Detection for Medical Visual Question Answering
Jiayi Chen, Benteng Ma, Zehui Liao +3
While medical Multimodal Large Language Models (MLLMs) have shown promise in assisting diagnosis, they still frequently generate hallucinated responses that appear linguistically p…
UniVRSE: Unified Vision-conditioned Response Semantic Entropy for Hallucination Detection in Medical Vision-Language Models
Zehui Liao, Shishuai Hu, Ke Zou +5
Vision-language models (VLMs) have great potential for medical image understanding, particularly in Visual Report Generation (VRG) and Visual Question Answering (VQA), but they may…
V-Loop: Visual Logical Loop Verification for Hallucination Detection in Medical Visual Question Answering
Mengyuan Jin, Zehui Liao, Yong Xia
Multimodal Large Language Models (MLLMs) have shown remarkable capability in assisting disease diagnosis in medical visual question answering (VQA). However, their outputs remain v…
Cycle Context Verification for In-Context Medical Image Segmentation
Shishuai Hu, Zehui Liao, Liangli Zhen +2
In-context learning (ICL) is emerging as a promising technique for achieving universal medical image segmentation, where a variety of objects of interest across imaging modalities…
Instance-dependent Label Distribution Estimation for Learning with Label Noise
Zehui Liao, Shishuai Hu, Yutong Xie +1
Noise transition matrix (NTM) estimation is a promising approach for learning with label noise. It can infer clean posterior probabilities, known as Label Distribution (LD), based…
Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification
Zehui Liao, Shishuai Hu, Yanning Zhang +1
Addressing mixed closed-set and open-set label noise in medical image classification remains a largely unexplored challenge. Unlike natural image classification, which often separa…